Background: Guselkumab is an IL-23 inhibitor widely used for the treatment of moderate-to-severe plaque psoriasis. Our study aimed to characterize the profile of adverse events (AEs) associated with guselkumab from the FDA adverse event reporting system (FAERS).
Methods: Disproportionality analysis including the proportional reporting ratio (PRR), the reporting odds ratio (ROR), the Bayesian confidence propagation neural network (BCPNN), and the multiitem gamma Poisson shrinker (MGPS) algorithms were used to assess the signals of guselkumab related AE.
Results: A total of 22,950,014 reports were collected from the FAERS database, of which 24,312 reports regarding guselkumab as the 'primary suspected (PS)' AEs were identified. AEs induced by guselkumab were distributed in 27 organ systems. In this study, 205 significant disproportionality preferred terms (PTs) that matched four algorithms simultaneously were obtained for analysis. Unexpected significant AEs such as onychomadesis, malignant melanoma in situ, endometrial cancer, and erectile dysfunction were observed.
Conclusion: The clinical observed AEs, along with potential new AE signals associated with guselkumab were identified based on the analysis of FAERS data, which could provide valuable evidence for clinical monitoring, risk identification, and further safety studies of identification.
Keywords: Disproportionality analysis; FAERS; data mining; guselkumab; pharmacovigilance.